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Side Effect Prediction Using Cooperative Pathways

机译:协同途径的副作用预测

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Drugs and biological experiments are designed to affect a particular target gene or pathway. However, they might inadvertently activate other pathways and cause side effects.Because of the existence of complex cellular mechanisms responding to stimuli,it is difficult to detect the presence of such side effects.Therefore, identification of pathways that function together under identical conditions would greatly help in anticipating these side effects before conducting these experiments. We develop a novel method to enumerate ``cooperative pathways'''' defined as pathways that functiontogether under identical conditionsby combining pathway networks withcomprehensive gene expression profiles.For finding cooperative pathways from whole pathways,we propose an efficient algorithm, CoopeRativE Pathway Enumerator (CREPE),which enumerates connected subpathways having common activate conditionsand selects combinations of the subpathways sharing the conditions.%We apply CREPE to a yeast stress dataset combined with the KEGG pathways.We observe that the starch and sucrose metabolism pathwaycooperates with the pyruvate metabolism under heat shock stresses. It cooperates with the tricarboxylic acid (TCA) cycle under the stationary phases.
机译:药物和生物学实验旨在影响特定的目标基因或途径。然而,它们可能会无意间激活其他途径并引起副作用。由于存在复杂的细胞机制来响应刺激,因此很难检测到此类副作用的存在。因此,鉴定在相同条件下共同起作用的途径将大有裨益。在进行这些实验之前,有助于预测这些副作用。我们开发了一种新颖的方法来枚举被定义为在相同条件下共同发挥作用的途径的``合作途径'',方法是将途径网络与全面的基因表达谱相结合。为从整个途径中寻找合作途径,我们提出了一种有效的算法CoopeRativE途径枚举器(CREPE) ),它列举了具有共同激活条件的相连子途径,并选择了共享条件的子途径的组合。%我们将CREPE应用于结合KEGG途径的酵母应激数据集。我们观察到淀粉和蔗糖代谢途径与热休克下的丙酮酸代谢协同作用压力。它与固定相下的三羧酸(TCA)循环配合使用。

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